Thermodynamics of the gas-phase dimerization of formic acid: Fully anharmonic finite temperature calculations at the CCSD(T) and many DFT levels

Dávid Vrška, Michal Pitoňák, Tomáš Bučko
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Abstract

A proof-of-concept study is undertaken to demonstrate the utility of the machine learning combined with the thermodynamic perturbation theory (MLPT) to test the accuracy of electronic structure methods in finite-temperature thermodynamic calculations. As a test example, formic acid dimer is chosen, which is one of the systems included in the popular benchmark set S22 [Jurečka et al., Phys. Chem. Chem. Phys. 8, 1985–1993 (2006)]. Starting from the explicit molecular dynamics and thermodynamic integration performed at the PBE + D2 level, the MLPT is used to obtain fully anharmonic dimerization free and internal energies at the reference quality CCSD(T) level and 19 different density functional approximations, including GGA, meta-GGA, non-local, and hybrid functionals with and without dispersion corrections. Our finite-temperature results are shown to be both qualitatively and quantitatively different from those obtained using the conventional benchmarking strategy based on fixed structures. The hybrid functional HSE06 is identified as the best performing approximate method tested, with the errors in free and internal energies of dimerization being 36 and 41 meV, respectively.
甲酸气相二聚化的热力学:在 CCSD(T) 和许多 DFT 水平上进行的全非谐波有限温度计算
为了证明机器学习与热力学扰动理论(MLPT)相结合在有限温度热力学计算中测试电子结构方法准确性的实用性,我们进行了一项概念验证研究。我们选择了甲酸二聚物作为测试实例,它是流行的基准集 S22 [Jurečka 等人,《物理化学》(Phys. Chem. Chem. Phys. 8, 1985-1993 (2006)]中的系统之一。从在 PBE + D2 水平上进行的显式分子动力学和热力学积分开始,利用 MLPT 在参考质量 CCSD(T) 水平和 19 种不同的密度泛函近似(包括 GGA、元 GGA、非局部和带或不带色散修正的混合泛函)上获得完全非谐波二聚化自由能和内能。结果表明,我们的有限温度结果与使用基于固定结构的传统基准策略得到的结果在质和量上都有所不同。混合函数 HSE06 被认为是测试中性能最好的近似方法,二聚化的自由能和内能误差分别为 36 和 41 meV。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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